Abstract 382: Risk Prediction Algorithm Accurately Identifies Patients at High Risk for 30-Day Readmission after Percutaneous Coronary Intervention

Background: Approximately 15% of Medicare patients who undergo percutaneous coronary intervention (PCI) are readmitted to the hospital within 30 days of discharge. A risk prediction algorithm which accurately identifies PCI patients’ risk for readmission may provide an opportunity to implement strategies to optimize care transitions to reduce inpatient readmissions and hospitalization costs in higher risk patients. Methods: We retrospectively applied a published validated 30-day readmission risk prediction algorithm to all PCI cases across three high volume centers within a single health care system between July 1, 2009 and September 30, 2013. Readmission risk scores were calculated and cases were grouped by low- (<6), intermediate- (6-10) and high-risk (≥11). Inpatient readmissions were compared between groups. Based on 4.25-year historical data and mean total variable costs per inpatient readmission, we assessed the impact of reducing the readmission rate by 50% in high-risk patients and 30% in intermediate-risk patients on readmissions per year and annual total variable costs. Results: Among 13,494 PCI cases, 1,237 (9.2%) were high-, 5,846 (43.3%) were intermediate- and 6,411 (47.5%) were low-risk. High-, intermediate- and low-risk groups had significantly different overall readmission rates (19.8% vs. 10.5% vs. 5.4%; p<0.001) (Figure). On average, there were 283 readmissions per year, and the mean total variable costs were $6,530 per inpatient readmission. Reducing readmissions by 50% in high-risk patients and 30% in intermediate-risk patients would reduce 72 inpatient readmissions per year and result in total variable costs savings of $470,160 annually. Conclusions: A risk prediction algorithm accurately identifies PCI patients at highest risk for hospital readmission. This tool may enable providers to implement targeted strategies to reduce 30-day readmissions and hospital costs through transition care conferences, registered nurse telephone contact, early clinical follow-up and care management.